The Unmanned Aerial Vehicles (UAVs) are aircrafts capable of flying and realizing amission without people on board. Originally developed as part of military activities,there is now great potential for civilian activities (monitoring, mapping...). Manyconstraints remain unresolved for the use of UAV in public space. Among the key aspectsto be tackled are embedded decision autonomy, the ability to perceive the environmentat all times, safety and dependability. These characteristics will in future be subject toa certification process under development, but current UAVs still suffering from a lackof robustness and autonomy.The flight control systems (combining Inertial Measurement Unit, sensors, motors,actuators...) provide stability and control functions and navigation of UAVs. Forexample, an inertial unit, is necessary to calculate the attitude of the UAV in flight, isoften composed mainly of triads of MEMS (Micro-Electro-Mechanical Systems)accelerometers, magnetometers and gyroscopes. These sensors are prone to defaults(magnetic disturbances, biases...) which subsequently affects the control system (thecalculation of the attitude of the UAV and its stability in flight).Many approaches for the attitude estimation are still unreliable and often drift overtime. Preliminary works have been developed in [1], [2] and possible improvements inthe strategies of robust estimation, combining inertial, magnetic data and / or GPS, arestill possible. On the other hand, the purely tele-operated control of an UAV, especiallyin a cluttered environment is a delicate task that must be facilitated by the autonomousexecution of local actions such as for monitoring or avoidance of obstacles.In this context, the proposed thesis can be developed in two parts with the followingobjectives:- In the first part of the thesis, we will focus on the problem of attitude estimation(3D spatial orientation) of the UAV. This information is often necessary fornavigation (stabilization of the UAV) in flight condition. The results of previousworks in literature at this level are encouraging but significant discrepancies arestill observed in the attitude estimation in case of sudden and acceleratedmovements of the UAV [3]. To solve this problem, we propose new data fusionapproaches based on complementary filtering for the states estimation andobservation by combining inertial measurements (accelerometers and gyroscopes)and magnetic measurements (magnetometers) and without resorting at each timeto GPS and velocity measurements.The proposed methods until now for the attitude estimation in the case of UAVsare based on the triad of sensors mentioned latter; we will search if it is possibleat a final step to overcome the gyro data and its intrinsic bias. In this case themethod will be reduced to the use of accelerometer and magnetometer.- In the second part of the thesis, we will develop some fault-tolerant controls(sensors and actuators defaults, but also real-time execution defaults and / orloss of connection with the master station) using the sensors measurements andthe available execution resources.The approaches we propose will be based on the design of observers for the isolation and estimation of defaults, as well as the design and implementation ofrobust control laws and flexible real-time scheduling.